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China is getting better at keeping its own AI researchers, but that does not mean it has become a leading destination for foreign talent. A 2026 Carnegie Endowment for International Peace analysis of NeurIPS authors finds that more Chinese-origin researchers are working in China than in 2022, while the U.S.–China talent-flow balance remains strongly in the United States’ favor. The findings describe a growing domestic research ecosystem—and a separate challenge in attracting researchers from abroad.
What the NeurIPS data say about AI talent in China and the U.S.
Carnegie’s analysis uses authors of papers accepted at NeurIPS, a major AI research conference, as a measure of where some leading researchers studied and work. For the 2025 conference, the study counted 5,823 accepted papers and 25,677 unique authors. Its career-flow comparisons cover 10,280 authors—40 percent of that cohort—with recorded undergraduate education, graduate education, and current workplace.
The study’s headline comparisons are:
| Measure | China | United States |
|---|---|---|
| Share of the sampled AI talent working in the country in 2025 | 41 percent | 34 percent |
| Chinese-origin researchers working in the country in 2025 | 69 percent of researchers with undergraduate degrees from China | Among researchers working in the U.S., the share with undergraduate degrees from China rose by 4 percentage points from 2022 |
| U.S.–China origin-to-workplace flow balance in 2025 | 30 to 1, still largely in the United States’ favor | |
These figures answer different questions. The 41 and 34 percent figures describe the workplace distribution of the sampled AI talent. “Chinese-origin” means a researcher earned an undergraduate degree in China; it does not mean the person’s nationality or birthplace. The 69 percent figure measures how many of those Chinese-origin researchers were working in China.
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No. Carnegie compares each researcher’s undergraduate origin with their current workplace. The 30-to-1 figure is an origin-to-workplace talent-flow measure, not a count of people who migrated between the two countries during 2025. It does not show when anyone moved, or whether their career path involved a move at all.
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The comparison also relies on the 10,280 authors whose three-stage histories were complete. Carnegie says broader sample checks preserve the main U.S.–China findings, but the complete-history group is not assumed to be a random sample. Country classification follows the listed institution or employer; for a multinational company, that can mean its home country rather than the researcher’s physical office.
China is retaining more of its own AI researchers
The clearest change is in China’s ability to keep researchers who began their education there. In Carnegie’s comparison, 69 percent of researchers with undergraduate degrees from China were working in China in 2025, up from 57 percent in 2022. China also accounted for 57 percent of the cohort’s undergraduate degrees in 2025, an increase of 11 percentage points from 2022.
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Those are related but distinct signs of a stronger domestic pipeline: more of the conference-author cohort began its higher education in China, and a larger share of Chinese-origin researchers were working there. Neither measure establishes that researchers returned from the United States, since the study does not report migration timing.
Carnegie’s reporting points to a broader set of research opportunities inside China, including universities, major technology companies, and startups. DeepSeek and Moonshot have raised the profile of domestic AI work. Tencent’s appointment of former OpenAI researcher Yao Shunyu as chief AI scientist is another example of a prominent role being created at home. These cases illustrate the range of opportunities; they do not quantify foreign recruitment or explain any individual hiring decision.
Why recruiting foreign researchers is a different challenge
A strong homegrown research scene can make China more attractive to Chinese-origin researchers without making it equally attractive to researchers from other countries. Carnegie’s reporting describes several competing considerations: U.S. universities, startups, and research funding remain appealing, while moving to a country with a different language and relatively few immigrants can be difficult.
Policy and geopolitics may also affect choices. Carnegie identifies tighter U.S. visa conditions, domestic industry opportunities, and changed geopolitical conditions as factors that could shape whether Chinese-origin researchers go to the United States or remain in China. The study does not measure the relative effect of visas, compensation, language, research freedom, or other considerations, so these are contextual explanations—not a causal ranking.
The distinction matters: keeping domestic graduates is not the same task as persuading foreign researchers to relocate. The NeurIPS analysis provides evidence about researchers’ education and listed workplaces, but it does not isolate foreign recruitment or establish why an individual chose one country over another.
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The U.S. still draws Chinese-origin researchers
The data do not support a simple story that U.S.–China tensions have caused Chinese-origin researchers to leave the United States in large numbers. Carnegie’s study finds that the share of U.S.-working researchers who had undergraduate degrees from China increased by 4 percentage points between 2022 and 2025.
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Damien Ma, who led the study, said: “Despite U.S.-China tensions, the number of Chinese-origin researchers working in the U.S. actually rose by four percentage points rather than declined.” That finding concerns the share of researchers working in the United States who earned undergraduate degrees in China; it does not show that geopolitical tensions had no effect on other researchers or on future hiring.
How far to generalize from the study
NeurIPS authors are a selective, conference-based group, not a census of AI researchers or a representative sample of all AI workers. The study is useful for comparing the education and workplaces of a visible research cohort, but it cannot by itself establish the balance of foreign hiring across the entire AI industry.
- It shows: where authors in the measured cohort studied and where their recorded current workplaces are based.
- It does not show: when researchers moved, whether they changed countries, or why they accepted a job or stayed.
- It does not establish: a causal ranking of salaries, visas, language, funding, political conditions, or research freedom.
The strongest conclusion is therefore specific: China’s domestic AI ecosystem has become more capable of retaining Chinese-origin researchers, while the measured U.S.–China talent-flow imbalance still favors the United States. That is evidence of progress at home, not proof that China has solved the separate problem of recruiting foreign AI researchers.
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